Locally mesh-refined lattice Boltzmann method for fuel debris air cooling analysis on GPU supercomputer

Naoyuki ONODERA, Yasuhiro IDOMURA, Shinichiro UESAWA, Susumu YAMASHITA, Hiroyuki YOSHIDA
2020 Mechanical Engineering Journal  
It is very important for nuclear design and safety to analyze thermal-hydrodynamics based on detailed computational fluid dynamics (CFD) simulations. This kind of heat transfer simulation is also an essential tool for decommissioning the TEPCO's Fukushima Daiichi nuclear power station (Nuclear Damage Compensation and Decommissioning Facilitation Corporation, 2017). A dry method is one of practical methods for retrieving debris from the reactor. To remove the decay heat from the fuel debris
more » ... ut water, it is necessary to predict thermal environments in the pedestal under the reactor pressure vessel (RPV) with high reliability. Japan Atomic Energy Agency (JAEA) has been developing a thermal hydraulic CFD code JUPITER, which is based on an incompressible Navier-Stokes model. JUPITER successfully evaluated the air cooling performance for the fuel debris in the dry method Uesawa et al., 2017) . However, in an incompressible fluid model, the pressure Poisson equation has to be solved iteratively with sparse matrix solvers. In reactor scale simulations, which are characterized by large-scale and complicated boundary, it is rather difficult to develop numerically robust and computationally efficient sparse matrix solvers. In addition, JUPITER is based on a uniform Cartesian grid system, and thus, requires large computational resources to capture multi-scale flows around complicated debris structures at the actual reactor scale. To resolve this issue, it is necessary to develop a new simulation code suitable for such large-scale Abstract A dry method is one of practical methods for decommissioning the TEPCO's Fukushima Daiichi nuclear power station. Japan Atomic Energy Agency (JAEA) has been evaluating the air cooling performance of the fuel debris by using the JUPITER code based on an incompressible fluid model and the CityLBM code based on the lattice Boltzmann method (LBM). However, these codes were based on a uniform Cartesian grid system, and required large computational time and cost to capture complicated debris structures and multi-scale flows at the actual reactor scale. The adaptive mesh refinement (AMR) method is one of the key techniques to accelerate multiscale simulations. We develop an AMR version of the CityLBM code on GPU based supercomputers and apply it to thermal-hydrodynamics problems. The proposed method is validated against free convective heat transfer experiments at JAEA. Thanks to the AMR method, grid resolution is optimized near the walls where velocity and temperature gradients are large, and the temperature distribution agrees with the experimental data using half the number of grid points. It is also shown that the AMR based CityLBM code on 4 NVIDIA TESLA V100 GPUs gives 6.7x speedup of the time to solution compared with the JUPITER code on 36 Intel Xeon E5-2680v3 CPUs. The results show that the AMR based LBM is promising for accelerating extreme scale thermal convective simulations.
doi:10.1299/mej.19-00531 fatcat:vkyeckd5u5ccbnaie3jr2kprdy